1. Field of the Invention
The present invention relates generally to an improved data processing system, and in particular, to a computer implemented method for predicting business metrics in a data processing environment. More particularly, the present invention relates to a computer implemented method, system, and computer usable program code for non-intrusive event-driven prediction in a data processing environment configured for business monitoring.
2. Description of the Related Art
In decision-making processes of a business, predicted values of certain business metrics are used for planning, budgeting, detecting errors, and many other purposes. For example, a business metric may be quarterly budget deficit that has been recorded for several quarters. The budget deficit (or surplus) of past quarters is often used as a basis for predicting budget deficits or surpluses for future quarters.
Certain metrics are called key performance indicators (KPI). Metrics, such as quarterly budget deficit or cost of a business operation, are measured and recorded periodically during the operation of a business process. The historical information of a metric is used for predicting the value of the metric at some time in the future. A KPI is an aggregation of a metric, for example, an average value of a metric over a period of one month.
A metric, including a KPI, is defined specifically for the process whose performance is being measured or predicted. Accordingly, detailed knowledge of the business process is necessary for the metric to be selected, observed, recorded, and forecasted properly. For example, cost of processing a claim may be a metric, but how that metric is to be measured and how that metric is to be predicted depends on which business process' cost of processing the metric represents. In other words, a metric that represents an insurance business' cost of processing a claim metric may be very different from a metric that represents a product manufacturer's cost of processing a claim.